In 1968, the American Standard Code for Information Interchange, better known by
its acronym ASCII, was standardized. ASCII defined numeric codes for various
characters, with the numeric values running from 0 to 127. For example, the
lowercase letter ‘a’ is assigned 97 as its code value.

ASCII was an American-developed standard, so it only defined unaccented
characters. There was an ‘e’, but no ‘é’ or ‘Í’. This meant that languages
which required accented characters couldn’t be faithfully represented in ASCII.
(Actually the missing accents matter for English, too, which contains words such
as ‘naïve’ and ‘café’, and some publications have house styles which require
spellings such as ‘coöperate’.)

For a while people just wrote programs that didn’t display accents. I remember
looking at Apple ][ BASIC programs, published in French-language publications in
the mid-1980s, that had lines like these:

PRINT"FICHIER EST COMPLETE."PRINT"CARACTERE NON ACCEPTE."

Those messages should contain accents, and they just look wrong to someone who
can read French.

In the 1980s, almost all personal computers were 8-bit, meaning that bytes could
hold values ranging from 0 to 255. ASCII codes only went up to 127, so some
machines assigned values between 128 and 255 to accented characters. Different
machines had different codes, however, which led to problems exchanging files.
Eventually various commonly used sets of values for the 128-255 range emerged.
Some were true standards, defined by the International Standards Organization,
and some were de facto conventions that were invented by one company or
another and managed to catch on.

255 characters aren’t very many. For example, you can’t fit both the accented
characters used in Western Europe and the Cyrillic alphabet used for Russian
into the 128-255 range because there are more than 127 such characters.

You could write files using different codes (all your Russian files in a coding
system called KOI8, all your French files in a different coding system called
Latin1), but what if you wanted to write a French document that quotes some
Russian text? In the 1980s people began to want to solve this problem, and the
Unicode standardization effort began.

Unicode started out using 16-bit characters instead of 8-bit characters. 16
bits means you have 2^16 = 65,536 distinct values available, making it possible
to represent many different characters from many different alphabets; an initial
goal was to have Unicode contain the alphabets for every single human language.
It turns out that even 16 bits isn’t enough to meet that goal, and the modern
Unicode specification uses a wider range of codes, 0-1,114,111 (0x10ffff in
base-16).

There’s a related ISO standard, ISO 10646. Unicode and ISO 10646 were
originally separate efforts, but the specifications were merged with the 1.1
revision of Unicode.

(This discussion of Unicode’s history is highly simplified. I don’t think the
average Python programmer needs to worry about the historical details; consult
the Unicode consortium site listed in the References for more information.)

A character is the smallest possible component of a text. ‘A’, ‘B’, ‘C’,
etc., are all different characters. So are ‘È’ and ‘Í’. Characters are
abstractions, and vary depending on the language or context you’re talking
about. For example, the symbol for ohms (Ω) is usually drawn much like the
capital letter omega (Ω) in the Greek alphabet (they may even be the same in
some fonts), but these are two different characters that have different
meanings.

The Unicode standard describes how characters are represented by code
points. A code point is an integer value, usually denoted in base 16. In the
standard, a code point is written using the notation U+12ca to mean the
character with value 0x12ca (4810 decimal). The Unicode standard contains a lot
of tables listing characters and their corresponding code points:

Strictly, these definitions imply that it’s meaningless to say ‘this is
character U+12ca’. U+12ca is a code point, which represents some particular
character; in this case, it represents the character ‘ETHIOPIC SYLLABLE WI’. In
informal contexts, this distinction between code points and characters will
sometimes be forgotten.

A character is represented on a screen or on paper by a set of graphical
elements that’s called a glyph. The glyph for an uppercase A, for example,
is two diagonal strokes and a horizontal stroke, though the exact details will
depend on the font being used. Most Python code doesn’t need to worry about
glyphs; figuring out the correct glyph to display is generally the job of a GUI
toolkit or a terminal’s font renderer.

To summarize the previous section: a Unicode string is a sequence of code
points, which are numbers from 0 to 0x10ffff. This sequence needs to be
represented as a set of bytes (meaning, values from 0-255) in memory. The rules
for translating a Unicode string into a sequence of bytes are called an
encoding.

The first encoding you might think of is an array of 32-bit integers. In this
representation, the string “Python” would look like this:

This representation is straightforward but using it presents a number of
problems.

It’s not portable; different processors order the bytes differently.

It’s very wasteful of space. In most texts, the majority of the code points
are less than 127, or less than 255, so a lot of space is occupied by zero
bytes. The above string takes 24 bytes compared to the 6 bytes needed for an
ASCII representation. Increased RAM usage doesn’t matter too much (desktop
computers have megabytes of RAM, and strings aren’t usually that large), but
expanding our usage of disk and network bandwidth by a factor of 4 is
intolerable.

It’s not compatible with existing C functions such as strlen(), so a new
family of wide string functions would need to be used.

Many Internet standards are defined in terms of textual data, and can’t
handle content with embedded zero bytes.

Generally people don’t use this encoding, instead choosing other encodings that
are more efficient and convenient.

Encodings don’t have to handle every possible Unicode character, and most
encodings don’t. For example, Python’s default encoding is the ‘ascii’
encoding. The rules for converting a Unicode string into the ASCII encoding are
simple; for each code point:

If the code point is < 128, each byte is the same as the value of the code
point.

If the code point is 128 or greater, the Unicode string can’t be represented
in this encoding. (Python raises a UnicodeEncodeError exception in this
case.)

Latin-1, also known as ISO-8859-1, is a similar encoding. Unicode code points
0-255 are identical to the Latin-1 values, so converting to this encoding simply
requires converting code points to byte values; if a code point larger than 255
is encountered, the string can’t be encoded into Latin-1.

Encodings don’t have to be simple one-to-one mappings like Latin-1. Consider
IBM’s EBCDIC, which was used on IBM mainframes. Letter values weren’t in one
block: ‘a’ through ‘i’ had values from 129 to 137, but ‘j’ through ‘r’ were 145
through 153. If you wanted to use EBCDIC as an encoding, you’d probably use
some sort of lookup table to perform the conversion, but this is largely an
internal detail.

UTF-8 is one of the most commonly used encodings. UTF stands for “Unicode
Transformation Format”, and the ‘8’ means that 8-bit numbers are used in the
encoding. (There’s also a UTF-16 encoding, but it’s less frequently used than
UTF-8.) UTF-8 uses the following rules:

If the code point is <128, it’s represented by the corresponding byte value.

If the code point is between 128 and 0x7ff, it’s turned into two byte values
between 128 and 255.

Code points >0x7ff are turned into three- or four-byte sequences, where each
byte of the sequence is between 128 and 255.

UTF-8 has several convenient properties:

It can handle any Unicode code point.

A Unicode string is turned into a string of bytes containing no embedded zero
bytes. This avoids byte-ordering issues, and means UTF-8 strings can be
processed by C functions such as strcpy() and sent through protocols that
can’t handle zero bytes.

A string of ASCII text is also valid UTF-8 text.

UTF-8 is fairly compact; the majority of code points are turned into two
bytes, and values less than 128 occupy only a single byte.

If bytes are corrupted or lost, it’s possible to determine the start of the
next UTF-8-encoded code point and resynchronize. It’s also unlikely that
random 8-bit data will look like valid UTF-8.

The Unicode Consortium site at <http://www.unicode.org> has character charts, a
glossary, and PDF versions of the Unicode specification. Be prepared for some
difficult reading. <http://www.unicode.org/history/> is a chronology of the
origin and development of Unicode.

Since Python 3.0, the language features a str type that contain Unicode
characters, meaning any string created using "unicoderocks!", 'unicoderocks!, or the triple-quoted string syntax is stored as Unicode.

To insert a Unicode character that is not part ASCII, e.g., any letters with
accents, one can use escape sequences in their string literals as such:

>>> "\N{GREEK CAPITAL LETTER DELTA}"# Using the character name'\u0394'>>> "\u0394"# Using a 16-bit hex value'\u0394'>>> "\U00000394"# Using a 32-bit hex value'\u0394'

In addition, one can create a string using the decode() method of
bytes. This method takes an encoding, such as UTF-8, and, optionally,
an errors argument.

The errors argument specifies the response when the input string can’t be
converted according to the encoding’s rules. Legal values for this argument are
‘strict’ (raise a UnicodeDecodeError exception), ‘replace’ (use U+FFFD,
‘REPLACEMENT CHARACTER’), or ‘ignore’ (just leave the character out of the
Unicode result). The following examples show the differences:

Encodings are specified as strings containing the encoding’s name. Python comes
with roughly 100 different encodings; see the Python Library Reference at
Standard Encodings for a list. Some encodings have multiple names; for
example, ‘latin-1’, ‘iso_8859_1’ and ‘8859’ are all synonyms for the same
encoding.

One-character Unicode strings can also be created with the chr()
built-in function, which takes integers and returns a Unicode string of length 1
that contains the corresponding code point. The reverse operation is the
built-in ord() function that takes a one-character Unicode string and
returns the code point value:

Another important str method is .encode([encoding],[errors='strict']),
which returns a bytes representation of the Unicode string, encoded in the
requested encoding. The errors parameter is the same as the parameter of
the decode() method, with one additional possibility; as well as ‘strict’,
‘ignore’, and ‘replace’ (which in this case inserts a question mark instead of
the unencodable character), you can also pass ‘xmlcharrefreplace’ which uses
XML’s character references. The following example shows the different results:

The low-level routines for registering and accessing the available encodings are
found in the codecs module. However, the encoding and decoding functions
returned by this module are usually more low-level than is comfortable, so I’m
not going to describe the codecs module here. If you need to implement a
completely new encoding, you’ll need to learn about the codecs module
interfaces, but implementing encodings is a specialized task that also won’t be
covered here. Consult the Python documentation to learn more about this module.

In Python source code, specific Unicode code points can be written using the
\u escape sequence, which is followed by four hex digits giving the code
point. The \U escape sequence is similar, but expects 8 hex digits, not 4:

Using escape sequences for code points greater than 127 is fine in small doses,
but becomes an annoyance if you’re using many accented characters, as you would
in a program with messages in French or some other accent-using language. You
can also assemble strings using the chr() built-in function, but this is
even more tedious.

Ideally, you’d want to be able to write literals in your language’s natural
encoding. You could then edit Python source code with your favorite editor
which would display the accented characters naturally, and have the right
characters used at runtime.

Python supports writing source code in UTF-8 by default, but you can use almost
any encoding if you declare the encoding being used. This is done by including
a special comment as either the first or second line of the source file:

The syntax is inspired by Emacs’s notation for specifying variables local to a
file. Emacs supports many different variables, but Python only supports
‘coding’. The -*- symbols indicate to Emacs that the comment is special;
they have no significance to Python but are a convention. Python looks for
coding:name or coding=name in the comment.

If you don’t include such a comment, the default encoding used will be UTF-8 as
already mentioned.

The Unicode specification includes a database of information about code points.
For each code point that’s defined, the information includes the character’s
name, its category, the numeric value if applicable (Unicode has characters
representing the Roman numerals and fractions such as one-third and
four-fifths). There are also properties related to the code point’s use in
bidirectional text and other display-related properties.

The following program displays some information about several characters, and
prints the numeric value of one particular character:

importunicodedatau=chr(233)+chr(0x0bf2)+chr(3972)+chr(6000)+chr(13231)fori,cinenumerate(u):print(i,'%04x'%ord(c),unicodedata.category(c),end=" ")print(unicodedata.name(c))# Get numeric value of second characterprint(unicodedata.numeric(u[1]))

The category codes are abbreviations describing the nature of the character.
These are grouped into categories such as “Letter”, “Number”, “Punctuation”, or
“Symbol”, which in turn are broken up into subcategories. To take the codes
from the above output, 'Ll' means ‘Letter, lowercase’, 'No' means
“Number, other”, 'Mn' is “Mark, nonspacing”, and 'So' is “Symbol,
other”. See
<http://www.unicode.org/Public/UNIDATA/UCD.html#General_Category_Values> for a
list of category codes.

Marc-André Lemburg gave a presentation at EuroPython 2002 titled “Python and
Unicode”. A PDF version of his slides is available at
<http://downloads.egenix.com/python/Unicode-EPC2002-Talk.pdf>, and is an
excellent overview of the design of Python’s Unicode features (based on Python
2, where the Unicode string type is called unicode and literals start with
u).

Once you’ve written some code that works with Unicode data, the next problem is
input/output. How do you get Unicode strings into your program, and how do you
convert Unicode into a form suitable for storage or transmission?

It’s possible that you may not need to do anything depending on your input
sources and output destinations; you should check whether the libraries used in
your application support Unicode natively. XML parsers often return Unicode
data, for example. Many relational databases also support Unicode-valued
columns and can return Unicode values from an SQL query.

Unicode data is usually converted to a particular encoding before it gets
written to disk or sent over a socket. It’s possible to do all the work
yourself: open a file, read an 8-bit byte string from it, and convert the string
with str(bytes,encoding). However, the manual approach is not recommended.

One problem is the multi-byte nature of encodings; one Unicode character can be
represented by several bytes. If you want to read the file in arbitrary-sized
chunks (say, 1K or 4K), you need to write error-handling code to catch the case
where only part of the bytes encoding a single Unicode character are read at the
end of a chunk. One solution would be to read the entire file into memory and
then perform the decoding, but that prevents you from working with files that
are extremely large; if you need to read a 2Gb file, you need 2Gb of RAM.
(More, really, since for at least a moment you’d need to have both the encoded
string and its Unicode version in memory.)

The solution would be to use the low-level decoding interface to catch the case
of partial coding sequences. The work of implementing this has already been
done for you: the built-in open() function can return a file-like object
that assumes the file’s contents are in a specified encoding and accepts Unicode
parameters for methods such as .read() and .write(). This works through
open()‘s encoding and errors parameters which are interpreted just
like those in string objects’ encode() and decode() methods.

Reading Unicode from a file is therefore simple:

f=open('unicode.rst',encoding='utf-8')forlineinf:print(repr(line))

It’s also possible to open files in update mode, allowing both reading and
writing:

The Unicode character U+FEFF is used as a byte-order mark (BOM), and is often
written as the first character of a file in order to assist with autodetection
of the file’s byte ordering. Some encodings, such as UTF-16, expect a BOM to be
present at the start of a file; when such an encoding is used, the BOM will be
automatically written as the first character and will be silently dropped when
the file is read. There are variants of these encodings, such as ‘utf-16-le’
and ‘utf-16-be’ for little-endian and big-endian encodings, that specify one
particular byte ordering and don’t skip the BOM.

In some areas, it is also convention to use a “BOM” at the start of UTF-8
encoded files; the name is misleading since UTF-8 is not byte-order dependent.
The mark simply announces that the file is encoded in UTF-8. Use the
‘utf-8-sig’ codec to automatically skip the mark if present for reading such
files.

Most of the operating systems in common use today support filenames that contain
arbitrary Unicode characters. Usually this is implemented by converting the
Unicode string into some encoding that varies depending on the system. For
example, Mac OS X uses UTF-8 while Windows uses a configurable encoding; on
Windows, Python uses the name “mbcs” to refer to whatever the currently
configured encoding is. On Unix systems, there will only be a filesystem
encoding if you’ve set the LANG or LC_CTYPE environment variables; if
you haven’t, the default encoding is ASCII.

The sys.getfilesystemencoding() function returns the encoding to use on
your current system, in case you want to do the encoding manually, but there’s
not much reason to bother. When opening a file for reading or writing, you can
usually just provide the Unicode string as the filename, and it will be
automatically converted to the right encoding for you:

Functions in the os module such as os.stat() will also accept Unicode
filenames.

os.listdir(), which returns filenames, raises an issue: should it return
the Unicode version of filenames, or should it return byte strings containing
the encoded versions? os.listdir() will do both, depending on whether you
provided the directory path as a byte string or a Unicode string. If you pass a
Unicode string as the path, filenames will be decoded using the filesystem’s
encoding and a list of Unicode strings will be returned, while passing a byte
path will return the byte string versions of the filenames. For example,
assuming the default filesystem encoding is UTF-8, running the following
program:

This section provides some suggestions on writing software that deals with
Unicode.

The most important tip is:

Software should only work with Unicode strings internally, converting to a
particular encoding on output.

If you attempt to write processing functions that accept both Unicode and byte
strings, you will find your program vulnerable to bugs wherever you combine the
two different kinds of strings. There is no automatic encoding or decoding if
you do e.g. str+bytes, a TypeError is raised for this expression.

It’s easy to miss such problems if you only test your software with data that
doesn’t contain any accents; everything will seem to work, but there’s actually
a bug in your program waiting for the first user who attempts to use characters
> 127. A second tip, therefore, is:

When using data coming from a web browser or some other untrusted source, a
common technique is to check for illegal characters in a string before using the
string in a generated command line or storing it in a database. If you’re doing
this, be careful to check the string once it’s in the form that will be used or
stored; it’s possible for encodings to be used to disguise characters. This is
especially true if the input data also specifies the encoding; many encodings
leave the commonly checked-for characters alone, but Python includes some
encodings such as 'base64' that modify every single character.

For example, let’s say you have a content management system that takes a Unicode
filename, and you want to disallow paths with a ‘/’ character. You might write
this code:

However, if an attacker could specify the 'base64' encoding, they could pass
'L2V0Yy9wYXNzd2Q=', which is the base-64 encoded form of the string
'/etc/passwd', to read a system file. The above code looks for '/'
characters in the encoded form and misses the dangerous character in the
resulting decoded form.